About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
ICDCS 2008
Conference paper
Enabling accurate node control in randomized duty cycling networks
Abstract
In this paper, we propose a novel duty cycling algorithm for a large-scale dense wireless sensor networks. The proposed algorithm is based on a social behavior of nodes in the sense that individual node's sleep/wakeup decision is influenced by the state of its neighbors. We analyze the behavior of the proposed duty cycling algorithm using a stochastic spatial process. In particular, we consider a geometric form of neighborhood dependence and a reversible Markov chain, and apply this model to analyze the behavior of the duty cycling network. We then identify a set of parameters for the reversible spatial process model, and study the steady state of the network with respect to these parameters. We report that our algorithm is scalable to a large network, and can effectively control the active node density while achieving a small variance. We also report that the social behavior of nodes has interesting and non-obvious impacts on the performance of duty cycling. Finally, we present how to set the parameters of the algorithm to obtain a desirable duty cycling behavior. © 2008 IEEE.